A dynamic size-based time series feature and application in identification of zinc flotation working conditions

Conventional feature description methods have large errors in froth features due to the fact that the image during the zinc flotation process of froth flotation is dynamic,and the existing image features rarely have time series information.Based on the conventional froth size distribution characteristics,this paper proposes a size trend core feature(STCF)considering the froth size distribution,i.e.,a feature centered on the time series of the froth size distribution.The core features of the trend are extracted,the inter-frame change factor and the inter-frame stability factor are given and two calculation methods of the feature factors are proposed.Meanwhile,the STCF feature algorithm was established based on the core features by adding the inter-frame change factor and the inter-frame stability factor.Finally,a flotation condition recognition model based on BP neural network was established.The experiments show that the recognition model has achieved excellent results,proving that the method proposed effectively overcomes the limitation of the lack of dynamic information in the existing traditional size distribution features and the introduction of the two factors can improve the classification accuracy to varying degrees.

New Adaptive Approach for Road Condition Identification in ASR Control System

A novel tire-road adaptive model in longitude direction to formulate the dynamic characteristic between tire and road is proposed in this paper, based on this model, a new adaptive approach of road condition identification is presented to identify the model＇s parameters on-line in order to improve the performance of anti-slip regulation system（ASR）. The optimal slip is determined by using the drive wheel＇s slip and longitude traction force in ASR before the slipping of the drive wheel. Co-simulation is done based on the model for JETTA GTX building with ADAMS/CAR and Matlab, and results show that the adaptive model accords with Pacejka model very well. This adaptive model has simpler form, less number of parameters and higher adaptability than usual, and the new identification approach has a small amounts of operation, which is very suitful for ASR.

Chassis Coordinated Control for Full X-by-Wire Vehicles-A Review

An X-by-wire chassis can improve the kinematic characteristics of human-vehicle closed-loop system and thus active safety especially under emergency scenarios via enabling chassis coordinated control.This paper aims to provide a complete and systematic survey on chassis coordinated control methods for full X-by-wire vehicles,with the primary goal of summarizing recent reserch advancements and stimulating innovative thoughts.Driving condition identification including driver’s operation intention,critical vehicle states and road adhesion condition and integrated control of X-by-wire chassis subsystems constitute the main framework of a chassis coordinated control scheme.Under steering and braking maneuvers,different driving condition identification methods are described in this paper.These are the trigger conditions and the basis for the implementation of chassis coordinated control.For the vehicles equipped with steering-by-wire,braking-by-wire and/or wire-controlled-suspension systems,state-of-the-art chassis coordinated control methods are reviewed including the coordination of any two or three chassis subsystems.Finally,the development trends are discussed.

Intelligent Fault-tolerant Management of Electromechanical Equipment

In this paper, a method of intelligent fault tolerant management on electromechanical equipment is presented. It is based on condition monitoring of equipment and realized by condition prediction and condition control. An example is introduced and analyzed in this paper.

High-effciency aircraft antiskid brake control algorithm via runway condition identification based on an on-off valve array

The aircraft antiskid braking system is an important hydraulic system for preventing tire bursts and ensuring safe take-off and landing. The brake system adjusts the force applied on the brake discs by controlling the brake pressure. Traditional aircraft antiskid braking systems achieve antiskid performance by controlling the braking pressure with an electrohydraulic servo valve.Because the pilot stage of an electrohydraulic servo valve is easily blocked by carbonized hydraulic oil, the servo valve would become a dangerous weak point for aircraft safety. This paper proposes a new approach that uses an on-off valve array to replace the servo valve for pressure control. Based on this new pressure control component, an efficient antiskid control algorithm that can utilize this discontinuous feature is proposed. Furthermore, the algorithm has the ability to identify the runway circumstances. To overcome the discontinuity in the process of using an on-off valve array, the Filippov framework is introduced. The conditions of convergence of the system are also discussed.The results of the digital simulations and the hardware-in-the-loop(HIL) braking experiments are used to verify the efficiency and stability of the proposed control algorithm. The method also proves that the on-off valve array can replace the servo valve perfectly as a new type of antiskid braking pressure control component.

Identification of working conditions and prediction of FeO content in sintering process of iron ore fines

The iron oxide(FeO)content had a significant impact on both the metallurgical properties of sintered ores and the economic indicators of the sintering process.Precisely predicting FeO content possessed substantial potential for enhancing the quality of sintered ore and optimizing the sintering process.A multi-model integrated prediction framework for FeO content during the iron ore sintering process was presented.By applying the affinity propagation clustering algorithm,different working conditions were efficiently classified and the support vector machine algorithm was utilized to identify these conditions.Comparison of several models under different working conditions was carried out.The regression prediction model characterized by high precision and robust stability was selected.The model was integrated into the comprehensive multi-model framework.The precision,reliability and credibility of the model were validated through actual production data,yielding an impressive accuracy of 94.57%and a minimal absolute error of 0.13 in FeO content prediction.The real-time prediction of FeO content provided excellent guidance for on-site sinter production.

Landmarks in the application of electrical tomography in particle science and technology

Selected milestones in the development and use of electrical tomography in powder conveying, slurry processing and multi-phase flow are highlighted. The ability to map concentration in opaque mixtures under process-realistic conditions was a major innovation for the method and has had far reaching implications. Subsequent developments have enabled velocity information to be abstracted resulting in the ability to measure component flux and motion.